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A novel approach to predicting exceptional growth in research
The prediction of exceptional or surprising growth in research is an issue with deep roots and few practical solutions. In this study, we develop and validate a novel approach to forecasting growth in highly specific research communities. Each research community is represented by a cluster of papers...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491740/ https://www.ncbi.nlm.nih.gov/pubmed/32931500 http://dx.doi.org/10.1371/journal.pone.0239177 |
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author | Klavans, Richard Boyack, Kevin W. Murdick, Dewey A. |
author_facet | Klavans, Richard Boyack, Kevin W. Murdick, Dewey A. |
author_sort | Klavans, Richard |
collection | PubMed |
description | The prediction of exceptional or surprising growth in research is an issue with deep roots and few practical solutions. In this study, we develop and validate a novel approach to forecasting growth in highly specific research communities. Each research community is represented by a cluster of papers. Multiple indicators were tested, and a composite indicator was created that predicts which research communities will experience exceptional growth over the next three years. The accuracy of this predictor was tested using hundreds of thousands of community-level forecasts and was found to exceed the performance benchmarks established in Intelligence Advanced Research Projects Activity’s (IARPA) Foresight Using Scientific Exposition (FUSE) program in six of nine major fields in science. Furthermore, 10 of 11 disciplines within the Computing Technologies field met the benchmarks. Specific detailed forecast examples are given and evaluated, and a critical evaluation of the forecasting approach is also provided. |
format | Online Article Text |
id | pubmed-7491740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74917402020-09-18 A novel approach to predicting exceptional growth in research Klavans, Richard Boyack, Kevin W. Murdick, Dewey A. PLoS One Research Article The prediction of exceptional or surprising growth in research is an issue with deep roots and few practical solutions. In this study, we develop and validate a novel approach to forecasting growth in highly specific research communities. Each research community is represented by a cluster of papers. Multiple indicators were tested, and a composite indicator was created that predicts which research communities will experience exceptional growth over the next three years. The accuracy of this predictor was tested using hundreds of thousands of community-level forecasts and was found to exceed the performance benchmarks established in Intelligence Advanced Research Projects Activity’s (IARPA) Foresight Using Scientific Exposition (FUSE) program in six of nine major fields in science. Furthermore, 10 of 11 disciplines within the Computing Technologies field met the benchmarks. Specific detailed forecast examples are given and evaluated, and a critical evaluation of the forecasting approach is also provided. Public Library of Science 2020-09-15 /pmc/articles/PMC7491740/ /pubmed/32931500 http://dx.doi.org/10.1371/journal.pone.0239177 Text en © 2020 Klavans et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Klavans, Richard Boyack, Kevin W. Murdick, Dewey A. A novel approach to predicting exceptional growth in research |
title | A novel approach to predicting exceptional growth in research |
title_full | A novel approach to predicting exceptional growth in research |
title_fullStr | A novel approach to predicting exceptional growth in research |
title_full_unstemmed | A novel approach to predicting exceptional growth in research |
title_short | A novel approach to predicting exceptional growth in research |
title_sort | novel approach to predicting exceptional growth in research |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491740/ https://www.ncbi.nlm.nih.gov/pubmed/32931500 http://dx.doi.org/10.1371/journal.pone.0239177 |
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